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Article
Publication date: 20 April 2015

Mouna Gazzah, Boubaker Jaouachi and Faouzi Sakli

The purpose of this paper is to predict the bagging recovery velocity of bagged denim fabric samples. Hence, the authors attempt to carry out a model highlighting and…

Abstract

Purpose

The purpose of this paper is to predict the bagging recovery velocity of bagged denim fabric samples. Hence, the authors attempt to carry out a model highlighting and explaining the impact of some considered frictional parameters such as yarn-to-yarn friction expressed as weft yarn rigidity parameter and metal-to-fabric friction expressed by mean frictional coefficient parameter.

Design/methodology/approach

The statistical analysis steps were implemented using experimental design type Taguchi and thanks to Minitab 14 software. The modeling methodology analyzed in this paper deals with the linear regression method application and analysis. The predictive power of the obtained model is evaluated by comparing the estimated recovery velocity (theoretical) with the actual values. These comparative values are measured after the bagging test and during the relaxation time of the denim fabric samples. The regression coefficient (R2) values as well as the statistical tests (p-values, analysis of variance results) were investigated, discussed and analyzed to improve the findings.

Findings

According to the statistical results given by Taguchi analysis findings, the regression model is very significant (p-regression=0.04 and R2=97 percent) which explains widely the possibility of bagging behavior prediction in the studied experimental field of interest. Indeed the variation (the increase or the decrease) of the frictional input parameters values caused, as a result, the variation of the whole appearance and the shape of the bagged zone expressed by the residual bagging height variations. In spite of their similar compositions and characteristics, the woven bagged fabrics presented differently behaviors in terms of the bagging recovery and kinetic velocity values. After relaxation times which are not the same and relative to different fabric samples, it may be concluded that bagging behavior remained function of the internal frictional stresses, especially yarn-to-yarn and metal-to-fabric ones.

Practical implications

This study is interesting for denim consumers and industrial applications during long and repetitive uses. The paper has practical implications in the clothing appearance and other textile industry, especially in the weaving process when friction forms (yarn-to-yarn, yarn-to-metal frictions) and stresses are drastic. In fact, in terms of the importance to the industrial producers of the materials it helps to provide a first step in an attempt for a better understanding of the stresses involved in bagging of woven fabrics in general and denim fabrics particularly due to important frictional input contributions. They provide the basis for the development of fabrics that can withstand bagging problems. This research may also put forward improved methods of measuring bagginess as function of frictional parameters in order to optimize (minimize) their effects on the bagging behaviors before and after repetitive uses. These experimental, statistical and theoretical findings may be used to predict bagginess of fabrics based on their properties and prevent industrial from the most significant and influential inputs which should be adjusted accurately. This work allows industrial, also, to make more attention, in case of a high-quality level to ensure, to optimize and review yarn behaviors used to produce fabrics against drastic solicitations and minimize frictions forms during experimental spinning and weaving processes.

Originality/value

Until now, there is no sufficient information to evaluate and predict the effect of the yarn-to-yarn friction as well as metal-to-yarn one on the residual bagging behavior. Besides, there is no work that deals with the kinetic recovery evolution as function of frictional inputs to explain accurately the bagging behavior evolution during relaxation time. Therefore, this present work is to investigate and model the residual bagging recovery velocity after bagging test as function of the frictional input parameters of both denim yarn and fabric samples (expressed by the friction caused due to contact from conformator to fabric).

Details

International Journal of Clothing Science and Technology, vol. 27 no. 2
Type: Research Article
ISSN: 0955-6222

Keywords

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Article
Publication date: 2 November 2015

Mouna Gazzah, Boubaker Jaouachi, Laurence Schacher, Dominique Charles Adolphe and Faouzi Sakli

The purpose of this paper is to predict the appearance of denim fabric after repetitive uses judging the denim cloth behavior and performance in viewpoint of bagging…

Abstract

Purpose

The purpose of this paper is to predict the appearance of denim fabric after repetitive uses judging the denim cloth behavior and performance in viewpoint of bagging ability. Hence, it attempts to carry out the significant inputs and outputs that have an influence on the bagging behaviors using the Principal Component Analysis (PCA) technique. In this study, the Kawabata Evaluation System parameters such as the frictional characteristics, the bending, compression, tensile and shear parameters are investigated to propose a model highlighting and explaining their impacts on the different bagging properties. To improve the obtained results, the selected significant inputs are also analyzed within their bagging properties using Taguchi experimental design. The linear regressive models prove the effectiveness of the PCA method and the obtained findings.

Design/methodology/approach

To investigate the mechanical properties and their contributions on the bagging characteristics, some denim fabrics were collected and measured thanks to the Kawabata evaluation systems (KES-FB1, KES-FB2, KES-FB3 and KES-FB4). These bagging properties were further analyzed applying the method of PCA to acquire factor patterns that indicate the most important fabric properties for characterizing the bagging behaviors of different studied denim fabric samples. An experimental design type Taguchi was, hence, applied to improve the results. Regarding the obtained results, it may be concluded that the PCA method remained a powerful and flawless technique to select the main influential inputs and significant outputs, able to define objectively the bagging phenomenon and which should be considered from the next researches.

Findings

According to the results, there are good relationships between the Kawabata input parameters and the analyzed bagging properties of studied denim fabrics. Indeed, thanks to the PCA, it is probably easy to reduce the number of the influent parameters for three reasons. First, applying this technique of selection can help to select objectively the most influential inputs which affect enormously the bagged fabrics. Second, knowing these significant parameters, the prediction of denim fabric bagging seems fruitful and can undoubtedly help researchers explain widely this complex phenomenon. Third, regarding the findings mentioned, it seems that the prevention of this aesthetic phenomenon appearing in some specific zones of denim fabrics will be more and more accurate.

Practical implications

This study is interesting for denim consumers and industrial applications during long and repetitive uses. Undoubtedly, the denim garments remained the largely used and consumed, hence, this particularity proves the necessity to study it in order to evaluate the bagging phenomenon which occurs as function of number of uses. Although it is fashionable to have bagging, the denim fabric remains, in contrast with the worsted ones, the most popular fabric to produce garments. Moreover, regarding this characteristic, the large uses and the acceptable value of denim fabrics, their aesthetic appearance behavior due to bagging phenomenon can be analyzed accurately because compared to worsted fabrics, they have a high value and the repetitive tests to investigate widely bagged zones may fall the industrial. The paper has practical implications in the clothing appearance and other textile industry, especially in the weaving process when friction forms (yarn-to-yarn, yarn-to-metal frictions) and stresses are drastic. This can help understanding why residual bagging behavior remained after garment uses due to the internal stress and excessive extensions. Regarding the selected influential inputs and outputs relative to bagging behaviors, there are some practical implications that have an impact on the industrial and researchers to study objectively the occurrence of this aesthetic phenomenon. Indeed, this study discusses the significance of the overall inputs; their contributions on the denim fabric bagged zones aims to prevent their ability to appear after uses. Moreover, the results obtained regarding the fabric mechanical properties can be useful to fabric and garment producers, designers and consumers in specifying and categorizing denim fabric products, insuring more denim cloth use and controlling fabric value. For applications where the subjective view of the consumer is of primary importance, the KES-FB system yields data that can be used for evaluating fabric properties objectively and prejudge the consumer satisfaction in viewpoint of the bagging ability. Therefore, this study shows that by measuring shear, tensile and frictional parameters of KES-FB, it may be possible to evaluate bagging properties. However, it highlights the importance and the significance of some inputs considered influential or the contrast (non-significant) in other researches.

Originality/value

This work presents the first study analyzing the bagged denim fabric applying the PCA technique to remove the all input parameters which are not significant. Besides, it deals with the relationship developed between the mechanical fabric properties (tensile, shear and frictional stresses) and the bagging properties behavior. To improve these obtained relationships, for the first time, the regression technique and experimental design type Taguchi analysis were both applied. Moreover, it is notable to mention that the originality of this study is to let researchers and industrials investigate the most influential inputs only which have a bearing on the bagging phenomenon.

Details

International Journal of Clothing Science and Technology, vol. 27 no. 6
Type: Research Article
ISSN: 0955-6222

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Article
Publication date: 2 November 2015

Mouna Gazzah, Boubaker Jaouachi and Faouzi Sakli

The purpose of this paper is to optimize the frictional input parameters related to the yarn and woven fabric samples. Indeed, using metaheuristic techniques for…

Abstract

Purpose

The purpose of this paper is to optimize the frictional input parameters related to the yarn and woven fabric samples. Indeed, using metaheuristic techniques for optimization, it helps to attempt the best quality appearance of garment, by analysing their effects and relationships with the bagging behaviour of tested fabrics before and after bagging test. Using metaheuristic techniques allows us to select widely the minimal residual bagging properties and the optimized inputs to adjust them for this goal.

Design/methodology/approach

The metaheuristic methods were applied and discussed. Hence, the genetic algorithms (GA) and ant colony optimization (ACO) technique results are compared to select the best residual bagging behaviour and their correspondent parameters. The statistical analysis steps were implemented using Taguchi experimental design thanks to Minitab 14 software. The modelling methodology analysed in this paper deals with the linear regression method application and analysis to prepare to the optimization steps.

Findings

The regression results are essential for evaluate the effectiveness of the relationships founded between inputs and outputs parameters and for their optimizations in the design of interest.

Practical implications

This study is interesting for denim consumers and industrial applications during long and repetitive uses. Undoubtedly, the denim garments remained the largely used and consumed, hence, this particularity proves the necessity to study it in order to optimize the bagging phenomenon which occurs as function of number of uses. Although it is fashionable to have bagging, the denim fabric remains, in contrast with the worsted ones, the most popular fabric to produce garments. Moreover, regarding this characteristic, the large uses and the acceptable value of denim fabrics, their aesthetic appearance behaviour due to bagging phenomenon can be analysed and optimized accurately because compared to worsted fabrics, they have a high value and the repetitive tests to investigate widely bagged zones can fall the industrial. The paper has practical implications in the clothing appearance and other textile industry, especially in the weaving process when friction forms (yarn-to-yarn, yarn-to-metal frictions) and stresses are drastic. This can help to understand why residual bagging behaviour remained after garment uses due to the internal stress and excessive extensions.

Originality/value

Until now, there is no work dealing with the optimization of bagging behaviour using metaheuristic techniques. Indeed, all investigations are focused on the evaluation and theoretical modelling based on the multi linear regression analysis. It is notable that the metaheuristic techniques such as ACO and GA are used to optimize some difficult problems but not yet in the textile field excepting some studies using the GA. Besides, there is no sufficiently information to evaluate, predict and optimize the effect of the yarn-to-yarn friction as well as metal-to-yarn one on the residual bagging behaviour. Several and different denim fabrics within their different characteristics are investigated to widen the experimental analysis and thus to generalize the results in the experimental design of interest.

Details

International Journal of Clothing Science and Technology, vol. 27 no. 6
Type: Research Article
ISSN: 0955-6222

Keywords

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Article
Publication date: 1 November 2014

M. Gazzah and B. Jaouachi

This work deals with the evolution of the residual bagging height of knitted samples. In comparing the results after a fabric bagging test, it may be concluded that the…

Abstract

This work deals with the evolution of the residual bagging height of knitted samples. In comparing the results after a fabric bagging test, it may be concluded that the behaviour of the sample length is an influential parameter which widely reflects the anisotropy of knitted structures. Hence, it is clear that the sample length does not exhibit the same behaviour in each knitted fabric zone which generally explains the impartial response after stress is applied. With regards to the different height values that the sample length presents in each measured part of the fabric, it may be concluded that there are several types of behaviours in the areas of bagging along the sample length. Moreover, it appears that there is a non uniform distribution of deformation after removing the stress. Therefore, internal stresses and deformations that cause different residual heights in the same sample accurately reflect and explain the anisotropic structure of the investigated knitted fabrics. In knowing that there is this non-uniform distribution of deformation, the input parameters also have considerable effects on the bending behaviour of the residual bagging. Indeed, when the yarn structure is changed, the residual bagging height changes too. Furthermore, our findings prove that elastic knitted fabrics accurately show a more minimal residual bagging height as opposed to non elastic fabrics in spite of the other input parameter values.

Details

Research Journal of Textile and Apparel, vol. 18 no. 4
Type: Research Article
ISSN: 1560-6074

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Article
Publication date: 12 September 2016

VIinay Kumar Midha, Shailja Sharma and Vaibhav Gupta

This paper aims to develop a single regression model (instead of developing models separately for each thread type) to predict the sewing thread consumption for cotton and…

Abstract

Purpose

This paper aims to develop a single regression model (instead of developing models separately for each thread type) to predict the sewing thread consumption for cotton and polyester staple spun threads.

Design/methodology/approach

A single regression model is developed for predicting sewing thread consumption for cotton and polyester threads. The polyester sewing threads have lower sewing thread consumption as compared to cotton threads because of their higher elongation behaviour. The model differentiates between the cotton and polyester sewing threads using their elongation values at peak levels of tensions experienced by the sewing threads during stitch tightening. By comparing the estimated thread consumption values with actual values, the effectiveness of model is evaluated with root mean square error and coefficient of determination (R2).

Findings

During the sewing process, by understanding the behaviour of different types of sewing threads, it is possible to develop a single regression model for all types of threads.

Practical implications

The sewing thread consumption can be easily calculated for cotton and polyester sewing threads using a single regression equation using the sewing assembly thickness, stitch density and elongation of thread at peak tension. The garment manufacturers need not depend on different charts for sewing thread consumption for stock management.

Originality/value

The sewing thread consumption is different for different types of threads, and garment manufacturers have to depend on different charts given by sewing thread manufacturers or use different equations for each type of threads. Using this single regression equation, sewing thread consumption for cotton and polyester sewing thread can be estimated accurately.

Details

Research Journal of Textile and Apparel, vol. 20 no. 3
Type: Research Article
ISSN: 1560-6074

Keywords

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Article
Publication date: 17 August 2021

Md Vaseem Chavhan, M. Ramesh Naidu and Hayavadana Jamakhandi

This paper aims to propose the artificial neural network (ANN) and regression models for the estimation of the thread consumption at multilayered seam assembly stitched…

Abstract

Purpose

This paper aims to propose the artificial neural network (ANN) and regression models for the estimation of the thread consumption at multilayered seam assembly stitched with lock stitch 301.

Design/methodology/approach

In the present study, the generalized regression and neural network models are developed by considering the fabric types: woven, nonwoven and multilayer combination thereof, with basic sewing parameters: sewing thread linear density, stitch density, needle count and fabric assembly thickness. The network with feed-forward backpropagation is considered to build the ANN, and the training function trainlm of MATLAB software is used to adjust weight and basic values according to the optimization of Levenberg Marquardt. The performance of networks measured in terms of the mean squared error and the layer output is set according to the sigmoid transfer function.

Findings

The proposed ANN and regression model are able to predict the thread consumption with more accuracy for multilayered seam assembly. The predictability of thread consumption from available geometrical models, regression models and industrial empirical techniques are compared with proposed linear regression, quadratic regression and neural network models. The proposed quadratic regression model showed a good correlation with practical thread consumption value and more accuracy in prediction with an overall 4.3% error, as compared to other techniques for given multilayer substrates. Further, the developed ANN network showed good accuracy in the prediction of thread consumption.

Originality/value

The estimation of thread consumed while stitching is the prerequisite of the garment industry for inventory management especially with the introduction of the costly high-performance sewing thread. In practice, different types of fabrics are stitched at multilayer combinations at different locations of the stitched product. The ANN and regression models are developed for multilayered seam assembly of woven and nonwoven fabric blend composition for better prediction of thread consumption.

Details

Research Journal of Textile and Apparel, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1560-6074

Keywords

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Article
Publication date: 18 November 2020

Md Vaseem Chavhan and Mandapati Ramesh Naidu

This paper aims to develop at sewing thread during the seam formation may lead to the compression of fabric under seam. In the present study, the model has been proposed…

Abstract

Purpose

This paper aims to develop at sewing thread during the seam formation may lead to the compression of fabric under seam. In the present study, the model has been proposed to predict the seam compression and calculation of seam boldness, as well as thread consumption by considering seam compression.

Design/methodology/approach

The effect of sewing parameters on the fabric compression at the seam (Cf) for fabrics of varying bulk density was studied by the Taguchi method and also the multilinear regression equation is obtained to predict seam compression by considering these parameters. The framework has been set as per the single view metrology approach to measuring structural seam boldness (Bs). One of the basic geometrical models (Ghosh and Chavhan, 2014) for the prediction of thread consumption at lock stitch has been modified by considering fabric compression at the seam (Cf).

Findings

The multilinear regression model has been proposed which can predict the compression under seam using easily measurable fabric parameters and stitch density. The seam boldness is successfully calculated quantitatively using the proposed formula with a good correlation with the seam boldness rated subjectively. The thread consumption estimation from the proposed approach was found to be more accurate.

Originality/value

The compression under seam is found out using easily measurable parameters; fabric thickness, fabric weight and stitch density from the proposed model. The attempt has been made to calculate seam boldness quantitatively and the new approach to find out thread consumption by considering the seam compression has been proposed.

Details

Research Journal of Textile and Apparel, vol. 25 no. 2
Type: Research Article
ISSN: 1560-6074

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Article
Publication date: 8 May 2018

Awadhesh Kumar Choudhary, Monica Puri Sikka and Payal Bansal

The purpose of this review paper is to define the dominating factors (such as fiber, yarn, fabric structure, sewing thread, sewing needle and machine parameters) that…

Abstract

Purpose

The purpose of this review paper is to define the dominating factors (such as fiber, yarn, fabric structure, sewing thread, sewing needle and machine parameters) that affect the seam damages and causing defects. It also describes the various explanations of sewing defects in garment production and critically analyzes them for optimum selection of parameters and speeds for minimizing such faults. Hence, the knowledge of various factors which affect the sewing damages/defects will be helpful for garment manufacturers/researchers to know influence of the parameters and control the quality of producing seam.

Design/methodology/approach

This section is not applicable for a review paper.

Findings

Sewing damages such as needle cut and other sewing damages/defects are studied mostly in woven fabric. There are very few studies conducted on knitted fabric sewing damages/defects. The sewing damage problems do not have single solution that is capable of removing these damages in fabric. All the determined and affecting parameters related to fiber, yarn, fabric construction, sewing thread and sewing machine must be examined to design appropriate remedial measurement related to machine design, fabric parameters and sewing thread. This could help in minimizing or eliminating the needle cut and other sewing damage problems.

Originality/value

It is an original review work and is helpful for garment manufacturers/researchers to reduce the defects and be able to produce good quality seam.

Details

Research Journal of Textile and Apparel, vol. 22 no. 2
Type: Research Article
ISSN: 1560-6074

Keywords

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